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Analyzing Contact Patterns in Public Transportation Systems for Opportunistic Communication Services
Eduardo R. Manika, Emilio C. G. Wille, Joilson Alves Jr
https://arxiv.org/abs/2506.02217

Analyzing Contact Patterns in Public Transportation Systems for Opportunistic Communication Services
Vehicle mobility has a significant impact on wireless communication between vehicles (buses) in Public Transportation Systems (PTS). Nevertheless, the transportation literature does not provide satisfactory models for bus movements because they are influenced by a variety of factors (itineraries, timetables, etc.). Custom-made mobility models that take these issues into account require a great deal of effort and may render simulations unfeasible. This article considers a tool (EMMS) that automa…

Pixel-Resolved Long-Context Learning for Turbulence at Exascale: Resolving Small-scale Eddies Toward the Viscous Limit
Junqi Yin, Mijanur Palash, M. Paul Laiu, Muralikrishnan Gopalakrishnan Meena, John Gounley, Stephen M. de Bruyn Kops, Feiyi Wang, Ramanan Sankaran, Pei Zhang
https://arxiv.org/abs/2507.16697

Pixel-Resolved Long-Context Learning for Turbulence at Exascale: Resolving Small-scale Eddies Toward the Viscous Limit
Turbulence plays a crucial role in multiphysics applications, including aerodynamics, fusion, and combustion. Accurately capturing turbulence's multiscale characteristics is essential for reliable predictions of multiphysics interactions, but remains a grand challenge even for exascale supercomputers and advanced deep learning models. The extreme-resolution data required to represent turbulence, ranging from billions to trillions of grid points, pose prohibitive computational costs for models b…